Mutant fate in spatially structured populations on graphs: Connecting models to experiments

Area of Science:

• Evolutionary biology
• Mathematical modeling
• Microbial evolution

Background:

• Spatial structure significantly influences microbial population evolution.
• Evolutionary graph theory predicts effects of spatial structures on mutant fixation.
• Discrepancies exist between theoretical assumptions and experimental evolution conditions.

Purpose of the Study:

• To bridge the gap between evolutionary graph theory and experimental evolution.
• To develop a novel model for spatially structured populations that mimics experimental conditions.
• To analyze recent experiments and propose future experimental designs.

Main Methods:

• Developed a new model for connected subpopulations on a graph with asymmetric migrations.
• The model explicitly incorporates serial passage events and large population sizes.
• Analyzed recent evolution experiments using the developed model.

Main Results:

• The model closely mimics conditions of modern evolution experiments.
• Identified useful parameter regimes for future experiments.
• Made quantitative predictions for experimental outcomes.

Conclusions:

• Asymmetric migrations on star graphs can suppress natural selection.
• This suppression can accelerate mutant fixation or extinction compared to well-mixed populations.
• Proposed specific experiments to test these predictions.